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Computing and Data Science Data Science

Ulster University, United Kingdom

MSc Internet of Things

Awarded by
Ulster University, United Kingdom
Course Code
Application Code
Study mode
Start Date
To be advised
2 years
Course Fee
HK$120,000 paid in 4 instalments
(subject to annual revision without prior notice)
Deadline on 31 Aug 2023 (Thu)
2587 3233
2571 8480
How to Apply


The programme aims to prepare students for both an industrial career with skills in the fields of networks, sensor technologies, pervasive computing, embedded systems, signal processing, security, statistical analysis and data analytics in addition to providing a relevant platform to embark on further research study. Students will also be able to apply the acquired skills in the development of Internet of Things (IoT) systems and applications. Students will be introduced all the core taught material and understand a range of topics and skills associated with the creation, evaluation and deployment of IoT systems and applications.

Upon completion of the programme, students should be able to:

Knowledge and Understanding

  1. demonstrate a comprehensive understanding of the advanced concepts, paradigms, algorithms, models, architectures and techniques underlying the computing and engineering domain of IoT;
  2. demonstrate a deep understanding of the underlying principles and practices associated with the deployment of different types of IoT systems and applications;
  3. effectively use practices and tools for the specification, design, implementation and critical evaluation from a technical perspective of IoT systems and applications;
  4. demonstrate a critical awareness of the professional, legal, moral and ethical issues surrounding the security and data issues associated with the deployment of IoT systems and applications;

Intellectual Qualities

  1. synthesise and critically review data from a range of sources to enable the specification, design and use embedded systems, pervasive computing systems, security architectures for networks, big data solutions and statistical models in the context of Internet of Things systems and applications;
  2. assess the implications, risks and security aspects of applying Internet of Things solutions to specific application domains;
  3. critically appraise and evaluate different types of Internet of Things components in applications in order to understand their interactions and to be able to improve, replace or create them;
  4. recognise and be able to respond in an appropriate way to opportunities for innovation;

Professional/Practical Skills

  1. demonstrate a comprehensive understanding of the complete engineering process involved in the effective deployment of IoT system and applications to solve practical problems in a variety of contexts;
  2. deploy effectively software and hardware tools towards the construction and documentation of IoT systems and applications;
  3. investigate and define a problem, identify constraints, understand customer and user needs, identify and manage cost drivers, social and ethical issues and data protection regulation issues, ensure fitness for purpose and manage the design process and evaluate outcomes.

Transferable Skills

  1. utilise digital and other learning resources and information retrieval skills to acquire, summarise and critically appraise information relevant to the IoT domain.
  2. demonstrate mastery of the translational skills necessary to communicate using rational and complex arguments, using a variety of media to technical and nontechnical audiences.
  3. demonstrate self-direction and originality in tackling and solving problems, and act autonomously in planning and implementing tasks to a professional standard.
  4. show originality and innovation and recognise the need for continuing professional development in the application of knowledge and techniques for the development of IoT systems.

Programme Details

Ulster University

Ulster University was established in 1968 as the New University of Ulster. It merged with Ulster Polytechnic in 1984 under the University of Ulster banner; incorporating its four campuses in Belfast, Coleraine, Magee College in Derry, and Jordanstown. The university has branch campuses in both London and Birmingham, and an extensive distance learning provision. The university rebranded as Ulster University from October 2014 and this included a revised visual identity.

Ulster University has a national and international reputation for excellence, innovation and regional engagement and continues to make a major contribution to the economic, social and cultural development of Northern Ireland. It is a leading modern university ranked 126-150th in the European Teaching Rankings 2018 and 150-200th in the Young University Rankings 2020 of The Times Higher Education.

Ulster University has an outstanding reputation for teaching and research, as evidenced by the outcomes of the National Student Survey (NSS) survey and the Research Excellence Framework. Coupled with the world class facilities and a practical focus, creates an educational experience that develops skills, raises ambitions and prepares future leaders.

Programme Structure

The entire programme comprises 7 modules (180 UK credits in total), to be completed in 24 months. Upon completion of 180 credits (at FHEQ level 6/7), students will be awarded a Master of Science Internet of Things. Upon completion of 120 credits (at FHEQ level 6/7), can be awarded a Postgraduate Diploma in Internet of Things.


Module Title

Year 1

Statistical Modelling and Data Mining

IoT Networks and Security

Pervasive Computing

Big Data and Infrastructure

Year 2

Digital Signal Processing

Embedded Systems and Sensors

Masters Project


Assessment for most modules is in the form of continuous assessments. Continuous assessment includes assignments, exercises, written reports, projects, presentations, practical skills assessments, portfolios and tests, depending on the nature of the modules.

News about the Internet of Things (IoT) Industry Development in Hong Kong:

Application Code 2245-IT084A -

Non-Local Higher and Professional Education (Regulation) Ordinance

This is an exempted course under the Non-local Higher and Professional Education (Regulation) Ordinance. It is a matter of discretion for individual employers to recognise any qualification to which this course may lead.


Statistical Modelling & Data Mining

Automated data collection tools lead to large amounts of data stored in databases, data warehouses and other information repositories. Automated data analytics and mining techniques are becoming essential components to any information system. The aim of this module is to equip students with a systematic understanding of knowledge of the underlying principles for the analysis of this data and the essential skills required for data mining and visualisation within complex, real-world context.

IoT Networks and Security

This module aims to:
  • Provide an appreciation of the IoT architecture and protocols.
  • Provide an understanding of the challenges associated with creating, securing and managing IoT networks.
  • Inform on the application of security for IoT networks, delving into subjects such as encryption, authentication and integrity.
  • Develop practical skills in the development and evaluation of IoT networks

Pervasive Computing

This module aims to:
  • Provide students with an opportunity to carry out a comprehensive research investigation of the various technologies utilised within pervasive computing;
  • Develop a critical awareness of the complex and emerging issues surrounding the design, development and evaluation of pervasive computing solutions. This will be facilitated through practical experience working with pervasive sensor technology and the data that can be collected from it;
  • Build a comprehensive understanding of research techniques through self-direction and autonomous working, making sound judgments and proposing new hypotheses to the application and usage of pervasive computing technologies;
  • Develop an appreciation for the social and ethical issues associated with pervasive computing and its application in a range of domains.

Big Data & Infrastructure

This module aims to understand the selection criteria and use case related to each class of database system.

Digital Signal Processing

This module aims to develop students with a deep understanding of digital signal processing with particular applications to sensors and relating IoT systems.

Embedded Systems and Sensors

This module aims:
  • To provide the student with extensive knowledge and to develop an understanding of the embedded systems hardware principles.
  • To provide the student with expertise in the programming of embedded systems. The software aspect of this module will focus on the development of C/C++ based software for embedded systems.
  • To develop student's expertise in critical evaluation and implementation of the embedded software using up to date industry standard design, debug and validation methods.
  • To apply the principles and concepts of the embedded systems design for the development of practical skills in the engineering of the microcontroller- based and programmable logic embedded systems applications.

Masters Project

The research project offers students an opportunity to complete a scholarly yet realistic piece of work during which material developed throughout the programme and extended through in-depth literature research can be related and applied to a problem drawn from a research area. The project tests the inventiveness, the critical capacities, the project management and the in-depth knowledge and problem-solving skills of students.

Class Details

Classes are delivered in weekday evenings (7-10pm) or weekends day time. Students will be arranged to study two 20-credit modules in each teaching block, and then they will have at least 7 months to prepare for and submit the Masters Project.


Application Fee

HK$150 (Non-refundable)

Course Fee
  • HK$120,000 paid in 4 instalments
    (subject to annual revision without prior notice)

Entry Requirements

Applicants shall:
 (a)     (i)   hold a degree with at least 2ii Honours division in computing, engineering or cognate area; OR
(ii) hold an equivalent qualification such as Graduate Diploma, Graduate Certificate, Postgraduate Certificate or Postgraduate Diploma in the subject areas of computing, engineering or related discipline.


(b)    provide evidence of competence in written and spoken English, such as
   (i) The honours degree (or equivalent) used as the basis for admission was taught and assessed in English; OR
   (ii) HKDSE English Language at Level 4 or above; OR
   (iii) HKALE Use of English at Grade D or above; OR
   (iv) HKASL Use of English at Grade D or above; OR
   (v) HKCEE English Language at Level 3 or above; OR
   (vi) an overall band of 6.0 with no subtests lower than 5.5 in the IELTS.




Application Form Download Application Form

Enrolment Method
Payment Method
1. Cash, EPS, WeChat Pay Or Alipay

Course fees can be paid by cash, EPS, WeChat Pay or Alipay at any HKU SPACE Enrolment Centres.

2. Cheque Or Bank draft

Course fees can also be paid by crossed cheque or bank draft made payable to “HKU SPACE”. Please specify the programme title(s) for application and the applicant’s name.. You may either:

  • bring the completed form(s), together with the appropriate course or application fees in the form of a cheque, and any required supporting documents to any of the HKU SPACE enrolment centres;
  • or mail the above documents to any of the HKU SPACE Enrolment Centres, specifying  “Course Application” on the envelope.  HKU SPACE will not be responsible for any loss of payment sent by mail.
3. VISA/Mastercard

Applicants may also pay the course fee by VISA or Mastercard, including the “HKU SPACE Mastercard”, at any HKU SPACE enrolment centres. Holders of the HKU SPACE Mastercard can enjoy a 10-month interest-free instalment period for courses with a tuition fee worth a minimum of HK$2,000; however, the course applicant must also be the cardholder himself/herself. For enquiries, please contact our staff at any enrolment centres.

4. Online Payment

Online application / enrolment is offered for most open admission courses (course enrolled on first come, first served basis) and selected award-bearing programmes. Application fees and course fees of these programmes/courses can be settled by using "PPS by Internet" (not available via mobile phones), VISA or Mastercard. In addition to the aforesaid online payment channels, continuing students of award-bearing programmes, if their programmes offer online service, may also pay their course fees by Online WeChat Pay, Online Alipay and Faster Payment System (FPS). Please refer to Enrolment Methods - Online Enrolment  for details.


  • If the programme/course is starting within five working days, application by post is not recommended to avoid any delays. Applicants are advised to enrol in person at HKU SPACE Enrolement Centres and avoid making cheque payment under this circustance.
  • Fees paid are not refundable except under very exceptional circumstances (e.g. course cancellation due to insufficient enrolment), subject to the School’s discretion. In exceptional cases where a refund is approved, fees paid by cash, EPS, WeChat Pay, Alipay, cheque or PPS (for online payment only) will normally be reimbursed by a cheque, and fees paid by credit card will normally be reimbursed to the payment cardholder's credit card account.
  • In addition to the published fees, there may be additional costs associated with individual programmes. Please refer to the relevant course brochures or direct any enquiries to the relevant programme team for details.
  • Fees and places on courses cannot be transferrable from one applicant to another. Once accepted onto a course, the student may not change to another course without approval from HKU SPACE. A processing fee of HK$120 will be levied on each approved transfer.
  • Receipts will be issued for fees paid but HKU SPACE will not be repsonsible for any loss of receipt sent by mail.
  • For payment certification, please submit a completed form, a sufficiently stamped and self-addressed envelope, and a crossed cheque for HK$30 per copy made payable to "HKU SPACE" to any of our enrolment centres.